Data Driven Identification and Cause Diagnosis of Online Academic Procrastination in Vocational Colleges

Academic procrastination is a bad study habit that is not only detrimental to the physical and mental health of learners, but also has a negative impact on academic achievement. Therefore, timely detection and intervention of learners' procrastination will help learners to complete their studies. This research uses the data of the procrastination assessment scale and the online learning platform as research tools, and compares the subjective willingness data of learners with the objective behavior data of the platform, and comprehensively analyzes the academic procrastination of higher vocational students in three different professional classes. The means clustering algorithm classifies the academic procrastination behaviors of students with similar behaviors. The research results show that the online academic procrastination of higher vocational students is generally not serious. There are three different types of learners in the course, namely high-frequency homework procrastinators, low-frequency homework procrastinators, and active learners. At the same time, this study supplemented the interview method to understand the reasons for students' procrastination. According to the interview results and the actual teaching situation, three intervention measures, group study, email reminder, and visual learning process, are proposed to reduce the number of students' delay in online study, improve the learner's learning initiative, and improve the effect of Vocational education.